63 lines
2.2 KiB
Python
63 lines
2.2 KiB
Python
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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""" Scripts that simplifies running training benchmark """
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import argparse
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import os
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import shutil
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import subprocess
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def main():
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# CLI flags
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parser = argparse.ArgumentParser(description="MaskRCNN train benchmark")
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parser.add_argument('--gpus', type=int, required=True)
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parser.add_argument('--batch_size', type=int, required=True)
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parser.add_argument('--amp', action='store_true')
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parser.add_argument('--data_dir', type=str, default='/data')
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parser.add_argument('--model_dir', type=str, default='/tmp/model')
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parser.add_argument('--weights_dir', type=str, default='/model')
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flags = parser.parse_args()
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main_path = os.path.abspath(os.path.join(os.path.dirname(__file__), '../mask_rcnn_main.py'))
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# build command
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cmd = (
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f'horovodrun -np {flags.gpus} '
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f'python {main_path}'
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f' --mode train'
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f' --model_dir "{flags.model_dir}"'
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f' --checkpoint "{os.path.join(flags.weights_dir, "resnet/resnet-nhwc-2018-10-14/model.ckpt-112602")}"'
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f' --training_file_pattern "{os.path.join(flags.data_dir, "train*.tfrecord")}"'
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f' --init_learning_rate 0.04'
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f' --total_steps 200'
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f' --use_batched_nms'
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f' --noeval_after_training'
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f' --nouse_custom_box_proposals_op'
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f' --xla'
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f' --train_batch_size {flags.batch_size}'
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f' {"--amp" if flags.amp else ""}'
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)
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# print command
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line = '-' * shutil.get_terminal_size()[0]
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print(line, cmd, line, sep='\n')
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# run model
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subprocess.call(cmd, shell=True)
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if __name__ == '__main__':
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main()
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